What is a “Balanced” Description? Insight from Parents of Individuals with Down Syndrome
Bibliographic record
Abstract
Genetic counselors and parents of individuals with Down syndrome (DS) agree that descriptions of DS in prenatal settings should be "balanced." However, there is no consensus regarding what constitutes a balanced description of DS. A survey was designed in collaboration with, and sent to the membership of, the British Columbia based Lower Mainland Down Syndrome Society (N = 260). Respondents were asked how they would describe DS to a couple who have just received a prenatal diagnosis of the condition. We rated the descriptions provided for positivity/negativity. Completed surveys were returned by 101 members, the majority of whom were Caucasian (87%) and female (79%). Participants' descriptions of DS ranged from entirely positive (n = 5; 10%) to entirely negative (n = 4; 7%) in nature. Deriving a description of DS that would broadly be perceived as "balanced" may be impossible. Instead, it may be more important to explore the range of possibilities regarding the family experience of raising a child with DS using nonjudgmental terminology, and to help families evaluate these possibilities in the context of their own values, coping strategies, and support networks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".